In a variety of visual applications, real-time tracking and analysis of vehicles, pedestrians, aircraft and other fast-moving objects can be said to be a breakthrough in security, automatic driving, smart city and other hot industries.
However, in order to achieve fast and accurate continuous tracking, there are many detected targets, mutual occlusion, distorted image, chaotic background, large difference in perspective, small target and fast speed.
▲ Video Reference public Data set [1][2][3][4]
So how do you acquire this ability quickly? What I’m going to show you today is not just a single intelligent vision algorithm, but a whole set of algorithmsMulti-function multi-scene Tracking system — PP-tracking.
It is a blend ofTarget detection, pedestrian re-recognition, trajectory fusionAnd optimize and solve the pain points and difficulties of the actual business targeted, provide pedestrian vehicle tracking, cross-shot tracking, multi-category tracking, small target tracking and flow count and other capabilities and industrial applications, but also support the development of visual interface, so that you quickly start, quickly land.
⭐ Project link ⭐Github.com/PaddlePaddl…Want to know the detailed structure, advantages and application of this super target tracking system? Let’s take you to a quick taste.
Rich function and good effect
Pp-tracking built-in DeepSORT[6], JDE[7] and FairMOT[8] three mainstream high-precision multi-target Tracking models, and a series of expansion and optimization for industrial pain points, combined with the actual landing scene, covering multi-category Tracking, cross-mirror Tracking, traffic statistics and other functions and applications. Can be described as precision, performance, functional rich everything. \
Single shot tracking
Single-category target tracking under a single shot refers to the continuous tracking of multiple targets in the same category under a single shot, which is the basis of tracking tasks. For this task, PP-tracking is based on the end-to-end One Shot high-precision model FairMOT[8], replaced byLighter backbone network HRnetv2-W18,Use a variety ofTricks, such as Sync_BN and EMA,Greatly improved accuracy while maintaining performance, And expand the training data set, reduce the input size,Finally, the accuracy of server side lightweight model is achieved on authoritative data set MOT17MOTA, 65.3, on the NVIDIA Jetson NXThe speed is 23.3FPS, GPU speed up to 60FPS! Meanwhile, PP-Tracking also provides high accuracy for high precision scenariosMOTA75.3High precision tracking model.
▲ Video Reference public data set [3]
>>Multicategory tracking
Pp-tracking can not only achieve a single type of target Tracking under a single shot with high performance, but also target Tracking scenarios of different types.Enhanced feature matching modules for different types of tracking tasks,Implement tracking category coveragePeople, bicycles, cars, trucks, buses, tricyclesWait for ten targets, accurately achieve a variety of different types of objects at the same time tracking.
▲ Video Reference public Data set [2]
* * * *>> Cross-shot tracking
Security scenes often involve continuous tracking of a target object in multiple shots. When the target switches from one shot to another, the target is often lost, at this time, a good effect and fast cross-shot tracking algorithm is essential! The cross-shot Tracking capability provided in PP-Tracking is based on DeepSORT[6] algorithm. Lightweight models developed by Baidu, PP-PicoDET and PP-LCNET, are used as detection models and ReID models respectively. In combination with the track fusion algorithm, high accuracy is taken into account while maintaining high performance. Implementation inCan you keep track of your target in multiple shots, no matter how many shots or scenes changeThe effect.
▲ Video Reference public Data set [2]
* * * *>> Traffic monitoring
At the same time, aiming at the high-frequency scenes in smart city —Human/vehicle flow monitoring, PP-Tracking also provides a complete solution, application server side lightweight version FairMOT[8] model to predict the target trajectory and ID information, to achieveReal-time de-counting of dynamic traffic flow/traffic flow, and support custom traffic statistics interval.
In order to meet the needs of different business scenarios, such as the flow monitoring at the entrance and exit of shopping malls, traffic monitoring at high-speed intersections, PP-Tracking is to provide traffic statistics on both sides of the entrance and exit.
▲ Video Reference public Data set [2]
Complex scenarios are covered
* * * *>> Pedestrian and vehicle trackingPedestrian and vehicle scenarios are particularly extensive in intelligent transportation, so PP-Tracking provides a comparison for pedestrians and vehiclesPretraining model, greatly reduce development costs, save training time and data costs, achieveBusiness scenario direct inference, algorithm is applicationThe effect of! Not only that, but PP-Tracking is supportedShow target orbit trace, more intuitively assist to achieve efficient path planning analysis.
▲ Video Reference public Data set [2]
>> The man’s head tracking
Moreover, in addition to having a strong versatility in daily tracking tasks, it often appears in practical businessSerious target occlusionAnd other problems, PP-tracking has also carried out a series of optimizations, providing a head Tracking model based on FairMOT[8] training, and in theHead Tracking 2021 data set tops the list,Help PP-Tracking flexibly adapt to various pedestrian scenarios.
▲ Video Reference public Data set [5]
>> Small target tracking
forSmall targets appear in large imagesPp-tracking is a series of optimizations for common industry problem scenarios, providing a pre-training model specifically for small target Tracking, which can achieve relatively accurate results in special scenarios, such as aerial shooting scenes such as drones.
▲ Video Reference public Data set [2]
Two usage modes
Practice reasoning dexterity
To meet different development needs, PP-Tracking can be used in two ways, whether you want to use code invocation/training model for rapid reasoning deployment, or you want to use the function directly with zero code.
>> API code call:
API simple and easy to use, support model call, training and reasoning deployment, minimize the development cost of the premise, flexible adaptation to various scenarios and tasks.
>> Visual development interface:
Include all functions and applications, without any development, can achieve all tasks, easy to integrate into all kinds of hardware.
Pp-tracking supports both Python and C++ deployment languages, and provides tutorials on Paddle Inference and Paddle Serving. Pp-tracking supports both Python and C++ deployment languages, and provides tutorials on Paddle Inference and Paddle Serving. Get through the whole process from training, reasoning to deployment in real sense. \
Rapid integration of industrial scenes
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How does such a powerful real-time tracking system perform in practice? Next, let’s take a look at pp-Tracking’s actual business implementation.
For example, in the actual business of Shanghai Yizhda Co., LTD., the lightweight version of FairMOT on the server of PP-Tracking [8] is used to quickly realize the real-time de-counting of people flow at the entrances and exits of the business circle in combination with the function of people flow counting.
▲ Video Reference public data set [3]
Has it been applied to target tracking in automatic driving, security, traffic, city and other fields?
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